Understanding how the brain processes complex signals is one of the fundamental goals of sensory neuroscience. These studies require one to be able to correlate the responses of sensory neurons to the complex sensory stimuli that elicited them. In the whisker primary somatosensory system (S1), these studies have traditionally proven challenging for two reasons: 1) Delivering spatiotemporally complex stimuli to multiple whiskers independently has been technically difficult, and 2) firing rates in S1 are often so low that it is not possible to acquire the amount of data needed to construct accurate receptive field estimates. This project has overcome these two constraints by developing a new multi-whisker stimulator system capable of stimulating a higher dimensional space than previously explored. Additionally, we have developed novel receptive field estimation methods that rely on subthreshold information rather than spikes. These advances allow us to collect in minutes the amount of data that would have taken hours to collect through traditional extra-cellular recordings. Furthermore, our method is capable of detecting nonlinear phenomena that are not detected by classically used receptive field analysis relying on spikes. Ours will be the first study that investigates the synaptic mechanisms underlying the processing of spatiotemporally complex stimuli in a cortical column of somatosensory cortex. This study will inform us how sensory cortices process complex stimulus information, as well as how the brain detects complex structural features in the sensory world. Through the use of whole- cell recordings and our new multi-whisker stimulator system, we will investigate how L4 integrates complex stimuli, which at the subthreshold level drives responses up to multiple whiskers away. We develop nonlinear analysis methods to show that L4 integrates multi-whisker inputs in a nonlinear fashion. These nonlinearities may be important for overcoming surround suppression in L4 during complex stimuli. Next we take advantage of our multi-whisker stimulator system to address response properties of neurons in L2/3. Specifically we are able to address the theory that L2/3 is using a sparse coding strategy to encode complex stimulus information. Through the use of a maximum noise entropy model, we are able to calculate the optimal stimulus for a L2/3 neuron online, and then deliver the stimulus back to the same neuron, thus making it fire. By driving spiking responses in L2/3 we will be able to determine whether L2/3 is employing a sparse coding regime, as well as what stimulus features L2/3 is sensitive to. Lastly, we will show that L5/6 neurons may be important for encoding structural features in the sensory environment. We will use our newly developed receptive field analysis techniques to probe the spatiotemporally complex receptive fields of deep layer neurons in S1. These receptive fields will inform us whether deeper layer neurons may be important for extracting structural features, encoded by temporal delays between whiskers. Our study will help move the field toward a unified understanding of how cortical microcircuits process complex and naturalistic information.